Pedro Bassi

Visiting PhD student at Johns Hopkins University, CCVL Lab. PhD student at the University of Bologna, Italy.

[Pedro Bassi @pedrorasb]

Happy to announce Merlin Plus: 25,494 CTs + reports, masks for tumors in 9 organs (first public CT masks for 6) & longitudinal data.

https://t.co/Jo0QyZz2mN

Thanks to @Zongwei_Zhou, @Dr_ASChaudhari, @curtlanglotz, @wenxuanli131, and all collaborators!

#MICCAI2026: Poster 173

[JHU Computer Science @JHUCompSci]

A team led by @Zongwei_Zhou has received a four-year R01 grant from @NIH to develop #AI algorithms capable of detecting three types of abdominal cancers on CT scans, enabling earlier diagnosis and treatment. https://t.co/yiWvivEW3Y

[Zongwei Zhou @Zongwei_Zhou]

A new TMI @IeeeTmi paper targets the false-negative problem (AI missing tumors in medical images) by creating synthetic “easy-to-miss” tumors based on radiology reports.

https://t.co/p9OWbDNNJz

This study has provided open-source code and models.

https://t.co/pC01eU9rsS

Collaboration with @Yale @nvidia @UCSF

[Zongwei Zhou @Zongwei_Zhou]

We are looking for collaboration to test our cancer-detection AI models worldwide. Wherever you are, join us!

https://t.co/qNnPg7ajEQ

[JHU Computer Science @JHUCompSci]

Our @CCVLatJHU researchers had a blast at @RSNA last week! #rsna2025

[Pedro Bassi @pedrorasb]

@MICCAI_Society Thank you very much for the opportunity to present our work!

[MICCAI Society @MICCAI_Society]

🙏 Thank you to Pedro Bassi for your presentation! 👏
#ICYMI: Watch the recording on RISE-MICCAI playlist on the #MICCAI Society YouTube channel.

🔗 https://t.co/8j2mgEzVod

[Pedro Bassi @pedrorasb]

@Zongwei_Zhou @RSNA @JohnsHopkins Thank you for all collaboration and guidance in this project!

[Zongwei Zhou @Zongwei_Zhou]

#RSNA25 @RSNA Oral presentation by Pedro Bassi @JohnsHopkins
Congrats @pedrorasb and team on receiving the RSNA 2025 Certificate of Merit Award and MICCAI 2025 Best Paper Award (Runner-up)!

Learning Segmentation from Radiology Reports https://t.co/gukCZGot2D

Paper: https://t.co/hE3pjGQXnP

[Zongwei Zhou @Zongwei_Zhou]

#RSNA25 @RSNA oral presentation by @wenxuanli131

Rewinding Late-Stage CT Scans to Train Al for Early Pancreatic Cancer Detection

https://t.co/f14UnacOEy

[JHU Computer Science @JHUCompSci]

In “16 Readily Available Radiology Reports Are Worth 1 Time-Consuming Voxel-Wise Annotation for Whole-Body CT Tumor Detection,” @pedrorasb, @wenxuanli131, @YuilleAlan, @Zongwei_Zhou, & more leverage #tumor info extracted from #radiology reports for detection of 7 tumors. (13/19)

[JHU Computer Science @JHUCompSci]

Researchers from @CCVLatJHU had 18 abstracts accepted to @RSNA’s #RSNA2025, with half chosen for oral presentations—a distinction afforded to only 7% of submissions! Check out the full list of accepted abstracts below or keep scrolling in this 🧵 (1/19)
https://t.co/QfdLQ8brga

[Zongwei Zhou @Zongwei_Zhou]

Detection of Tumors from Computed Tomography Scans Early and Pre-diagnostic https://t.co/CjOmkhDwva

[Pedro Bassi @pedrorasb]

🩻 See our ICCV poster on AbdomenAtlas 3.0 & RadGPT!

AbdomenAtlas 3.0: first public CT-Mask-Report dataset (9K CTs, 3K+ tumor CTs).

RadGPT: segmentation enables AI to write accurate tumor reports.

https://t.co/6P5MyNdhnK

📅 11:15 AM 📍Hall 1, Poster 369
#ICCV2025 @JHUCompSci

[JHU Computer Science @JHUCompSci]

Congratulations to @pedrorasb and team on the Best Paper Award Runner-Up recognition and to @jieneng_chen for receiving the @MICCAI_Society’s Doctoral Consortium 2025 Second Runner-Up Award at #MICCAI2025!

[JHU Computer Science @JHUCompSci]

@pedrorasb, @wenxuanli131, @Zongwei_Zhou, @YuilleAlan, @iethemhamamci, & @yy5ccuva present AbdomenAtlas 3.0, the 1st public, high-quality abdominal CT dataset w/ detailed radiology reports in “RadGPT: Constructing 3D Image-Text Tumor Datasets”: https://t.co/WNDumB4SlI (9/10)

[Zongwei Zhou @Zongwei_Zhou]

Congrats Pedro ! #MICCAI2025 Best Paper Award runner-up.

[Pedro Bassi @pedrorasb]

@Zongwei_Zhou Thank you very much, Zongwei!

[JHU Malone Center for Engineering in Healthcare @JHUMCEH]

In work appearing at @MICCAI_Society this week, JHU researchers including the Malone Center’s @Zongwei_Zhou demonstrate a new method that uses existing radiology reports to train #AI models to locate tumors on CT scans. Learn more: https://t.co/y6NwPzdqWn

[JHU Computer Science @JHUCompSci]

In work appearing at @MICCAI_Society, JHU’s @pedrorasb, @wenxuanli131, @jieneng_chen, @Tianyu_Linn, @YuilleAlan, & @Zongwei_Zhou demonstrate a new method that uses existing radiology reports to train #AI models to locate tumors on CT scans. Learn more: https://t.co/y6rkw4UtCb